NDLI: The independent detection of drought stress and leaf density using hyperspectral resolution data

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Effects of temperature, light, storage conditions, sowing time, and burial depth on the seed germination of Cardiocrinum cordatum var. glehnii (Liliaceae)

Landscape and Ecological Engineering : Volume 2

Landscape and Ecological Engineering : Volume 1

The independent detection of drought stress and leaf density using hyperspectral resolution data

Content Provider	Springer Nature Link
Author	Imanishi, Junichi Morimoto, Yukihiro Imanishi, Ayumi Sugimoto, Kayoko Isoda, Kazutaka
Copyright Year	2007
Abstract	Measurement of vegetation drought stress or leaf density is essential in ecosystem and agronomic studies. The normalized differential vegetation index (NDVI), a widely used vegetation index in remote sensing, seems to have some limitations as it is known to be affected by both drought stress and leaf density. A field experiment was conducted, using two-year-old potted Quercus serrata (a deciduous tree) and Q. glauca (an evergreen tree), to determine the optimal indices of vegetation drought stress or leaf density that have the least a simultaneous effect, and to test if the existing vegetation indices are useful for independently detecting drought stress or leaf density. The results showed that NDVI and similar indices, which utilize the difference or ratio between the reflectance of red and near infrared bands, such as the ratio vegetation index (RVI), the difference vegetation index (DVI), the atmospherically resistant vegetation index (ARVI), the renormalized difference vegetation index (RDVI), the enhanced vegetation index (EVI), the perpendicular vegetation index (PVI), soil-adjusted vegetation index (SAVI) and the improved variants of SAVI, were effective for the independent detection of leaf density but relatively ineffective for drought stress because they were significantly affected by leaf area index (LAI). Similarly, vegetation indices developed as detectors of vegetation stress, such as the water index (WI), the stress index (SI) and the derivative chlorophyll index (DCI), showed weak correlation (r) and partial correlation (r $_{p}$) with leaf water content (LWC). The optimal hyperspectral indices were proposed as (F $_{502.8}$ − F $_{852.0}$)/(F $_{502.8}$ + F $_{852.0}$) for LWC (r = 0.847, r $_{p}$ = 0.849) and R $_{750}$/R $_{550}$ (R750R550; Lichtenthaler et al. in J Plant Physiol 148:483–493, 1996) for LAI (r = 0.926, r $_{p}$ = 0.940) where R $_{ λ }$ and F $_{ λ }$ represent reflectance and first derivatives at wavelength λ nm, respectively. A simulation of lower spectral sampling intervals (ca. 3-nm intervals of original to 10-nm intervals) indicated that it will be necessary to check the appropriateness of the derivative indices approximate to the proposed indices before application because derivative spectra are less smooth as a function of wavelength than reflectance spectra.
Starting Page	55
Ending Page	65
Page Count	11
File Format	PDF
ISSN	18601871
Journal	Landscape and Ecological Engineering
Volume Number	3
Issue Number	1
e-ISSN	1860188X
Language	English
Publisher	Springer-Verlag
Publisher Date	2007-03-02
Publisher Place	Tokyo
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Water stress Leaf area index Hyperspectral remote sensing Tree canopy Vegetation indices Plant Ecology Landscape/Regional and Urban Planning Environmental Management Civil Engineering Nature Conservation Landscape Ecology
Content Type	Text
Resource Type	Article
Subject	Ecology Management, Monitoring, Policy and Law Nature and Landscape Conservation

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